167 Crewai Jobs - Page 4

As an experienced Python programmer, you will be responsible for developing GenAI applications and automation tools using your deep expertise in Python. Your role will involve the productionization of GenAI applications beyond Proof of Concepts (PoCs) by utilizing scale frameworks and tools such as Pylint and Pyrit. In addition to Python programming, you should be proficient in working with LLM Frameworks, including Autogen, Crew.ai, LangGraph, LlamaIndex, and LangChain. Your expertise in these frameworks will be essential for enhancing GenAI applications. Moreover, you will leverage your extensive experience with cloud platforms such as Azure, GCP, and AWS to deploy and manage GenAI applications effectively. Your knowledge of at least two of these cloud platforms will be crucial for the success of the projects. You should also possess mastery of fine-tuning techniques like PEFT, QLoRA, LoRA, and other methods to optimize the performance of GenAI applications. Your understanding of these techniques will contribute to the overall efficiency of the applications. Furthermore, your strong knowledge of LLMOps practices for model deployment, monitoring, and management will ensure the seamless operation of GenAI applications. Your expertise in LLMOps will be vital for the successful deployment and maintenance of models. As part of your role, you will be required to implement responsible AI practices and ensure compliance with regulations to uphold ethical standards. Your proficiency in Responsible AI will be essential for developing applications that align with ethical guidelines. Additionally, you should have experience in API integration using protocols such as REST, SOAP, and others. Your familiarity with API integration will enable seamless communication between different systems and enhance the functionality of GenAI applications.,

You will be responsible for designing, developing, and scaling the AI Agent Framework that powers automation-first modules in RevAi Pro, such as Tell Me, Action Center, and intelligent AI agents. This role is critical to shaping the core foundation of how automation, enterprise search, and just-in-time execution work inside our platform. Architect and implement the core orchestration engine for AI agents (event-driven/task-based). Manage agent lifecycle functions such as spawn, pause, escalate, and terminate. Enable secure, real-time communication between agents, services, and workflows. Integrate memory and retrieval systems using vector databases like Pinecone, Weaviate, or Qdrant. Integrate LLM providers (OpenAI, Azure OpenAI, Anthropic, Mistral, etc.) into agent workflows. Create modular prompt templates with retry/fallback mechanisms. Implement chaining logic and dynamic tool use for agents using LangChain or LlamaIndex. Develop reusable agent types such as Summarizer, Validator, Notifier, Planner, etc. Develop FastAPI-based microservices for agent orchestration and skill execution. Create APIs to register agents, execute agent actions, and manage runtime memory. Implement RBAC, rate limiting, and security protocols for multi-tenant deployments. Build connectors to integrate structured (CRM, SQL) and unstructured data sources (email, docs, transcripts). Route incoming data streams to relevant agents based on workflow and business rules. Support ingestion from tools like Salesforce, HubSpot, Gong, and Zoom. Deploy the agent platform using Docker and Kubernetes on Azure. Implement Redis, Celery, or equivalent async task systems for agent task queues. Set up observability to monitor agent usage, task success/failure, latency, and hallucination rates. Create CI/CD pipelines for agent modules and prompt updates. Ideal Candidate Profile: - 2-4 years of experience in backend engineering, ML engineering, or agent orchestration. - Strong command over Python (FastAPI, asyncio, Celery, SQLAlchemy). - Experience with LangChain, LlamaIndex, Haystack, or other orchestration libraries. - Hands-on with OpenAI, Anthropic, or similar LLM APIs. - Comfortable with vector embeddings and semantic search systems. - Understanding of modern AI agent frameworks like AutoGen, CrewAI, Semantic Planner, or ReAct. - Familiarity with multi-tenant API security and SaaS architecture. - Bonus: Frontend collaboration experience to support UI for agents and dashboards. - Bonus: Familiarity with SaaS platforms in B2B domains like RevOps, CRM, or workflow automation. What You'll Gain: - Ownership of agent architecture inside a live enterprise-grade AI platform. - Opportunity to shape the future of AI-first business applications. - Collaboration with founders, product leaders, and early enterprise customers. - Competitive salary with potential ESOP. - First-mover engineering credit on one of the most advanced automation stacks in SaaS.,

At Improzo, we are dedicated to improving life by empowering our customers through quality-led commercial analytical solutions. Founded by seasoned industry leaders, we have a dynamic team of experts in commercial data, technology, and operations who collaborate to shape the future. As a Senior Product Engineering Manager/Associate Director at Improzo, you will play a pivotal role in leading the development of our next-generation Analytics Platform with AI-Apps for the Life Sciences industry. In this role, you will leverage your technical expertise in Python, AI/ML, and data analytics to design and deliver a modern AI-first Analytical Apps platform. You will lead a team of engineers in building a platform that empowers users to solve key problems across the Life Sciences value chain by integrating AI Apps and actionable insights. Additionally, you will collaborate with product managers, architects, and business stakeholders to define the technical vision, strategy, and roadmap for the Analytics Platform. Key Responsibilities: - Design and deliver a modern AI-first Analytical Apps platform for the Life Sciences Industry. - Lead Platform Development, CI/CD/DevOps, Quality, Data Engineering, and ML Development & Ops. - Manage a team of software engineers specializing in Python (Django), data engineering, and AI/ML. - Collaborate with stakeholders to drive the integration of AI/ML capabilities into the Analytics Platform for advanced insights. - Ensure the platform provides robust capabilities for data exploration, analysis, visualization, and reporting. - Foster a collaborative, innovative, Agile, and high-performing engineering culture. - Provide technical guidance, mentorship, and career development support to team members. - Drive engineering best practices, code quality, and technical excellence within the team. - Participate in the recruitment and onboarding of new engineering talent. - Stay updated on the latest trends and technologies in analytics and artificial intelligence. Qualifications: - Bachelor's or master's degree in computer science or related disciplines. - 7+ years of product development experience leading engineering teams in a product-focused environment. - Proficiency in Python, data processing, analysis, backend development, and front-end technologies. - Strong understanding of data warehousing concepts, ETL/ELT processes, and data modeling. - Experience with cloud-based data platforms and services. - Expertise in integrating AI/ML models into applications and building agents. - Hands-on experience with CI/CD tools, containerization, monitoring, and logging tools. - Knowledge of pharmaceutical or biotech industry regulations and compliance requirements. - Strong problem-solving, analytical, and decision-making skills. - Strong leadership, mentoring, and coaching skills. Benefits: - Competitive salary and benefits package. - Opportunity to work on cutting-edge Analytics projects in the life sciences industry. - Collaborative and supportive work environment. - Opportunities for professional development and growth.,

You will be responsible for designing, building, and maintaining automated workflows using tools such as n8n, Make, Activepieces, Windmill.dev, or Coze. Your role will involve integrating APIs, databases, webhooks, and third-party services into workflows. Collaboration with cross-functional teams to understand automation needs and effectively translate them into efficient workflows will be a key aspect of your job. Additionally, you will have the opportunity to build and experiment with AI-powered flows using tools like LangChain, Flowise, or CrewAI. Testing, debugging, and optimizing workflows to ensure performance and reliability will also be part of your responsibilities. Documenting workflows, processes, and key automation logic for internal knowledge sharing is essential to facilitate seamless workflow management. The ideal candidate should have hands-on experience, whether through projects, freelance work, or personal initiatives, with at least one of the following tools: n8n, Coze, Make (Integromat), Activepieces, Windmill.dev, LangChain, Flowise, or CrewAI. A basic understanding of APIs, webhooks, and JSON is required, along with knowledge of workflow logic including triggers, conditions, loops, branching, and scheduling. Moreover, familiarity with integrating Software as a Service (SaaS) tools such as Slack, Gmail, Notion, and Airtable is beneficial for this role. A strong analytical and problem-solving mindset is essential to effectively tackle challenges that may arise during workflow automation. The willingness to learn and adapt to emerging tools and frameworks is crucial to stay updated and enhance your skills in this dynamic field.,

At EY, you'll have the chance to build a career as unique as you are, with the global scale, support, inclusive culture, and technology to become the best version of yourself. We are counting on your unique voice and perspective to help EY become even better. Join us and build an exceptional experience for yourself and contribute to creating a better working world for all. As an EY-Consulting AI Enabled Automation - GenAI/Agentic Manager, we are seeking individuals with strong AI Enabled Automation skills who are passionate about applying AI in the process automation space, including Azure, AI, ML, Deep Learning, NLP, GenAI, large Lang Models (LLM), RAG, Vector DB, Graph DB, and Python. Responsibilities: - Develop and implement AI-enabled automation solutions aligned with business objectives. - Design and deploy Proof of Concepts (POCs) and Points of View (POVs) across various industry verticals to showcase the potential of AI-enabled automation applications. - Ensure seamless integration of optimized solutions into the overall product or system. - Collaborate with cross-functional teams to understand requirements, integrate solutions into cloud environments (Azure, GCP, AWS), and align with business goals and user needs. - Educate the team on best practices and stay updated on the latest tech advancements to bring innovative solutions to the project. Technical Skills Requirements: - 9 to 13 years of relevant professional experience, proficiency in Python, and frameworks like PyTorch, TensorFlow, Hugging Face Transformers. - Strong foundation in ML algorithms, feature engineering, and model evaluation. - Proficiency in Deep Learning, Neural Networks, RNNs, CNNs, LSTMs, Transformers (BERT, GPT), and NLP. - Experience in GenAI technologies, LLMs (GPT, Claude, LLaMA), prompting, fine-tuning. - Knowledge of retrieval augmented generation (RAG) and Knowledge Graph RAG. - Experience with multi-agent orchestration, memory, and tool integrations. - Experience implementing MLOps practices and tools (CI/CD for ML, containerization, orchestration, model versioning, and reproducibility). - Experience with cloud platforms (AWS, Azure, GCP) for scalable ML model deployment. - Strong understanding of data pipelines, APIs, and distributed systems. - Ability to build observability into AI systems latency, drift, performance metrics. - Strong communication, presentation, client service, and technical writing skills in English for both technical and business audiences. - Strong analytical, problem-solving, and critical thinking skills. - Ability to work under tight timelines for multiple project deliveries. What We Offer: At EY GDS, we support you in achieving your unique potential both personally and professionally. We provide stretching and rewarding experiences that keep you motivated, working in an atmosphere of integrity and teaming with some of the world's most successful companies. While we encourage you to take personal responsibility for your career, we support your professional development in every way possible. You have the flexibility to devote time to what matters to you, in both your business and personal lives. At EY, you can be yourself, express your point of view, energy, and enthusiasm, no matter where you are in the world. This is how you can make a difference. EY | Building a better working world: EY exists to build a better working world, helping to create long-term value for clients, people, and society, and build trust in the capital markets. Enabled by data and technology, diverse EY teams in over 150 countries provide trust through assurance and help clients grow, transform, and operate. Working across assurance, consulting, law, strategy, tax, and transactions, EY teams ask better questions to find new answers for the complex issues facing our world today.,

Senior GenAI & Agentic AI Expert (Architect) Relocation to Abu Dhabi, UAE Location: Abu Dhabi Client: Abu Dhabi Government About The Role Our client, a global consulting firm with distributed teams across the US, Canada, UAE, India, and PK, is hiring a high-caliber Senior Generative AI Expert with proven hands-on experience in building Agentic AI applications . This role is ideal for someone who has a total of 12 to 20+ years of software engineering and AI/ML experience and is now focused on autonomous AI agents, tool-using LLMs, LangChain, AutoGPT, or similar frameworks . Key Responsibilities Design and develop Agentic AI applications using LLM frameworks (LangChain, AutoGPT, CrewAI, Semantic Kernel, or similar) Architect and implement multi-agent systems for enterprise-grade solutions Integrate AI agents with APIs, databases, internal tools, and external SaaS products Lead and mentor a cross-functional team across global time zones Optimize performance, context retention, tool usage, and cost efficiency Build reusable pipelines and modules to support GenAI use cases at scale Ensure enterprise-grade security, privacy, and compliance standards in deployments Collaborate directly with clients and senior stakeholders Ideal Candidate Profile 10 to 15+ years of professional experience in software engineering and AI/ML 3+ years of practical experience in LLM-based application development Strong track record of delivering Agentic AI systems (not just chatbot interfaces) Hands-on experience with: LangChain, AutoGPT, CrewAI, ReAct, Semantic Kernel OpenAI, Claude, Gemini, Mistral, or Llama2 Embedding models, vector databases (FAISS, Pinecone, Weaviate, etc.) Prompt engineering, RAG, memory/context management Serverless, Python, Node.js, AWS/GCP/Azure cloud Experience leading engineering teams and working with enterprise clients Excellent communication, documentation, and stakeholder management skills Must be open to relocation to UAE Why Join Work on UAE Government project(s) Lead cutting-edge Agentic AI projects at enterprise scale Collaborate with senior teams across US, Canada, UAE, India, and PK Competitive compensation + long-term career roadmap Skills: memory/context management,apis integration,enterprise-grade security,crewai,saas products integration,aws,semantic kernel,prompt engineering,openai,node.js,multi-agent systems,azure,databases integration,gemini,cost efficiency,embedding models,rag,autogpt,performance optimization,llm frameworks,agentic ai,generative ai,langchain,gcp,python,vector databases Show more Show less

At EY, you'll have the chance to build a career as unique as you are, with the global scale, support, inclusive culture, and technology to become the best version of you. And we're counting on your unique voice and perspective to help EY become even better, too. Join us and build an exceptional experience for yourself, and a better working world for all. We are looking to hire individuals with strong AI Enabled Automation skills who are interested in applying AI in the process automation space using technologies such as Azure, AI, ML, Deep Learning, NLP, GenAI, large Lang Models (LLM), RAG, Vector DB, Graph DB, and Python. Responsibilities: - Development and implementation of AI enabled automation solutions, ensuring alignment with business objectives. - Design and deploy Proof of Concepts (POCs) and Points of View (POVs) across various industry verticals to demonstrate the potential of AI enabled automation applications. - Ensure seamless integration of optimized solutions into the overall product or system. - Collaborate with cross-functional teams to understand requirements, integrate solutions into cloud environments (Azure, GCP, AWS, etc.), and ensure alignment with business goals and user needs. - Educate the team on best practices and keep updated on the latest tech advancements to bring innovative solutions to the project. Technical Skills Requirements: - 9 to 13 years of relevant professional experience. - Proficiency in Python and frameworks like PyTorch, TensorFlow, Hugging Face Transformers. - Strong foundation in ML algorithms, feature engineering, and model evaluation (Must). - Strong foundation in Deep Learning, Neural Networks, RNNs, CNNs, LSTMs, Transformers (BERT, GPT), and NLP (Must). - Experience in GenAI technologies such as LLMs (GPT, Claude, LLaMA), prompting, fine-tuning. - Experience with LangChain, LlamaIndex, LangGraph, AutoGen, or CrewAI (Agentic Framework). - Knowledge of retrieval augmented generation (RAG) and Knowledge Graph RAG. - Experience with multi-agent orchestration, memory, and tool integrations. - Experience/implement MLOps practices and tools (CI/CD for ML, containerization, orchestration, model versioning, and reproducibility) Good to have. - Experience with cloud platforms (AWS, Azure, GCP) for scalable ML model deployment. - Good understanding of data pipelines, APIs, and distributed systems. - Build observability into AI systems latency, drift, performance metrics. - Strong written and verbal communication, presentation, client service, and technical writing skills in English for both technical and business audiences. - Strong analytical, problem-solving, and critical thinking skills. - Ability to work under tight timelines for multiple project deliveries. What we offer: At EY GDS, we support you in achieving your unique potential both personally and professionally. We give you stretching and rewarding experiences that keep you motivated, working in an atmosphere of integrity and teaming with some of the world's most successful companies. While we encourage you to take personal responsibility for your career, we support you in your professional development in every way we can. You enjoy the flexibility to devote time to what matters to you, in your business and personal lives. At EY, you can be who you are and express your point of view, energy, and enthusiasm, wherever you are in the world. It's how you make a difference. EY | Building a better working world: EY exists to build a better working world, helping to create long-term value for clients, people, and society and build trust in the capital markets. Enabled by data and technology, diverse EY teams in over 150 countries provide trust through assurance and help clients grow, transform, and operate. Working across assurance, consulting, law, strategy, tax, and transactions, EY teams ask better questions to find new answers for the complex issues facing our world today.,

???? We&aposre Hiring: Artificial Intelligence Consultant! ???? We&aposre seeking a highly motivated and technically adept Artificial Intelligence Consultant to join our growing Artificial Intelligence and Business Transformation practice. This role is ideal for a strategic thinker with a strong blend of leadership, business consulting acumen, and technical expertise in Python, LLMs, Retrieval-Augmented Generation (RAG), and agentic systems. Experience Required: Minimum 6+ Years Location: Remote/ Work From Home Job Type: Contract to hire (1 Year /Renewable Contract) Notice Period: Immediate to 15 Days Max Mode of Interview: Virtual Roles And Responsibilities AI Engagements: Independently manage end-to-end delivery of AI-led transformation projects across industries, ensuring value realization and high client satisfaction. Strategic Consulting & Roadmapping: Identify key enterprise challenges and translate them into AI solution opportunities, crafting transformation roadmaps that leverage RAG, LLMs, and intelligent agent frameworks. LLM/RAG Solution Design & Implementation: Architect and deliver cutting-edge AI systems using Python, LangChain, LlamaIndex, OpenAI function calling, semantic search, and vector store integrations (FAISS, Qdrant, Pinecone, ChromaDB). Agentic Systems: Design and deploy multi-step agent workflows using frameworks like CrewAI, LangGraph, AutoGen or ReAct, optimizing tool-augmented reasoning pipelines. Client Engagement & Advisory: Build lasting client relationships as a trusted AI advisor, delivering technical insight and strategic direction on generative AI initiatives. Hands-on Prototyping: Rapidly prototype PoCs using Python and modern ML/LLM stacks to demonstrate feasibility and business impact. Thought Leadership: Conduct market research, stay updated with the latest in GenAI and RAG/Agentic systems, and contribute to whitepapers, blogs, and new offerings. Essential Skills Education : Bachelor&aposs or Masters in Computer Science, AI, Engineering, or related field. Experience : Minimum 6 years of experience in consulting or technology roles, with at least 3 years focused on AI & ML solutions. Leadership Quality: Proven track record in leading cross-functional teams and delivering enterprise-grade AI projects with tangible business impact. Business Consulting Mindset: Strong problem-solving, stakeholder communication, and business analysis skills to bridge technical and business domains. Python & AI Proficiency: Advanced proficiency in Python and popular AI/ML libraries (e.g., scikit-learn, PyTorch, TensorFlow, spaCy, NLTK). Solid understanding of NLP, embeddings, semantic search, and transformer models. LLM Ecosystem Fluency: Experience with OpenAI, Cohere, Hugging Face models; prompt engineering; tool/function calling; and structured task orchestration. Independent Contributor: Ability to own initiatives end-to-end, take decisions independently, and operate in fast-paced environments. Preferred Skills Cloud Platform Expertise: Strong familiarity with Microsoft Azure (preferred), AWS, or GCP including compute instances, storage, managed services, and serverless/cloud-native deployment models. Programming Paradigms: Hands-on experience with both functional and object-oriented programming in AI system design. Hugging Face Ecosystem: Proficiency in using Hugging Face Transformers, Datasets, and Model Hub. Vector Store Experience: Hands-on experience with FAISS, Qdrant, Pinecone, ChromaDB. LangChain Expertise: Strong proficiency in LangChain for agentic task orchestration and RAG pipelines. MLOps & Deployment: CI/CD for ML pipelines, MLOps tools (MLflow, Azure ML), containerization (Docker/Kubernetes). Cloud & Service Architecture: Knowledge of microservices, scaling strategies, inter-service communication. Programming Languages: Proficiency in Python and C# for enterprise-grade AI solution development. Show more Show less

???? Senior AI/ML Engineer Multi-Agent & MCP Architect Location: Mumbai (Hybrid) Company: Fin 100X.AI Indias Protocol-Governed AI Financial OS ???? Company Description Fin 100X.AI is Indias first protocol-governed, AI-powered Financial Operating System built for Bharats 100 crore underserved citizens. We are reimagining finance through: Multi-agent AI orchestration (MCP protocol-driven) Explainable and trustworthy AI Regulatory-first design (RBI, SEBI, IRDAI, PFRDA aligned) Backed by IIT Bombay alumni and top fintech leaders, we are building AI for Bharat that blends technology, trust, and inclusion. ???? Role Overview As a Senior AI/ML Engineer (MCP + Multi-Agent Orchestration), you will be part of the founding tech braintrust that defines the core AI architecture of Fin 100X.AI. Your mission: Design and deploy a world-class, multi-agent AI stack powered by MCP (Model Context Protocol) to deliver scalable, explainable, and reliable AI-driven financial advisory modules for 100 crore users. You will directly influence: AI Laxmi orchestration Credit Booster, SIP Planner, Fraud Shield National-scale agentic financial intelligence ???? Key Responsibilities Architect and implement multi-agent AI systems using MCP protocol Build LLM orchestration pipelines (LangChain, AutoGen, CrewAI, MCP) Design retrieval-augmented pipelines (RAG) with vector memory & routing Deploy neural models (NLP, NLU, recommendation engines) at scale Create fallback, routing, and governance layers for explainable AI Integrate real-time financial intelligence APIs (OpenAI, Gemini, HuggingFace, etc.) Mentor junior AI engineers; enforce best practices in ML Ops and agent orchestration Collaborate with backend/frontend teams for end-to-end AI productionization ? Required Qualifications Core Technical Skills Strong foundation in ML/DL architectures, NLP, and LLMs Expertise in multi-agent orchestration frameworks: MCP, AutoGen, CrewAI, LangGraph Advanced experience with Python (TensorFlow, PyTorch, HuggingFace, FastAPI) Proficient in vector search systems (Pinecone, FAISS, ChromaDB) Deep knowledge of RAG pipelines, memory graphs, prompt chaining Experience deploying models in cloud-native and microservice architectures Preferred Exposure FinTech AI systems or regulated AI environments Agent evaluation, explainability, and safety-first design Scaling AI in hybrid production (cloud + edge) environments ???? What We Value Architect mindset with hands-on coding skills Self-driven innovation and ownership from concept ? deployment Experience building AI systems for 10M+ scale Passion for financial inclusion, Bharat-first AI, and AI for Good ???? Perks Shape Indias AI Financial OS from Day 0 ESOP track + leadership growth National showcase at Global FinTech Fest 2025 Mentorship with IIT Bombay alumni & top AI architects Solve real Bharat-scale problems with MCP-first AI innovation Show more Show less

As a US-based tech company with a global reach, DXFactor is renowned for being a certified Great Place to Work. Currently, we are seeking talented individuals for the position of AI Architect / Tech Lead AI at our Ahmedabad location. In this role, you will be at the forefront of developing a cutting-edge AI video marketing system that revolutionizes the traditional content creation process. The focus will be on leveraging AI technology to not only edit or repurpose content, but to generate, orchestrate, and deploy marketing content autonomously through AI agents. Your responsibilities will include designing Agentic AI Systems for Content Creation, where you will architect AI workflows that enable agents to collaborate in analyzing, scripting, editing, generating, and optimizing marketing videos using advanced technologies such as LLMs, vision models, and orchestration layers. Additionally, you will lead the development of Multi-Agent Pipelines by building intelligent systems that utilize frameworks like LangChain, AutoGen, or CrewAI to coordinate agents for various tasks such as scripting, visual editing, channel adaptation, voice/speech synthesis, and A/B testing. Moreover, you will apply AI to real-world video marketing use cases by using diverse content sources like UGC, branded, and influencer content to generate customized marketing assets suitable for different platforms. You will also be responsible for generating Synthetic Media when necessary, by integrating tools like Runway, Synthesia, Pika, or ElevenLabs to create or enhance content components. Furthermore, as the Lead Architect, you will be tasked with integrating AI systems with various components of the marketing stack including Content Management Systems (CSMs), Digital Asset Management (DAM) systems, ad tech APIs (Meta, TikTok, Google Ads), social platforms (YouTube, Instagram), and performance tools (Google Analytics, Segment, attribution platforms). Your role will encompass not only designing the architecture but also hands-on development, ensuring seamless integration and functionality across the marketing ecosystem.,

You are a skilled Data Engineer / AI/ML Developer with a strong expertise in Python and AI/ML, responsible for building and scaling production-grade systems using LLMs. Your role involves working on real-world AI integrations, APIs, and cloud deployments within a fast-paced, growth-focused team. Your key responsibilities include building AI/LLM systems using OpenAI, Anthropic, etc., working with frameworks like LangChain, CrewAI, or AutoGen, developing APIs with Flask/FastAPI and async patterns, integrating databases (PostgreSQL/MySQL) and REST APIs, deploying on AWS, GCP, or Azure, writing clean, testable, production-grade Python code, and translating business needs into technical solutions. To excel in this role, you must have 2+ years of experience with LLM APIs and 1+ AI project in production, 3+ years of Python development experience, familiarity with function calling, prompt design (ReAct, CoT), cloud deployment (any platform), Git workflows, and testing. Additionally, you should possess strong debugging, error handling, and system design skills, along with the ability to work independently and collaborate cross-functionally. A preferred background would include a degree in CS or equivalent experience (bootcamp, self-taught, etc.), along with a portfolio showcasing live AI projects or GitHub repos. Knowledge of Vector DBs (Pinecone/Weaviate), Docker, and exposure to fintech would be considered as a bonus. Cloud or AI certifications, as well as experience in fintech or data-heavy domains, are nice-to-have skills for this role.,

Project Overview We are seeking a Senior Agentic AI Engineer to lead the design and development of an enterprise-grade Agentic AI framework. This framework will empower various business units across the organization to build intelligent, autonomous agents capable of handling complex workflows, using tools, interacting with APIs, and making decisions with minimal human intervention.This role requires deep expertise in architecting scalable, modular AI systems using LLMs, tool integration, memory systems, and agent orchestration. This role is ideal for someone who has hands-on experience with agentic AI frameworks like LangGraph, CrewAI and AutoGPT and a deep understanding of enterprise software engineering and system architecture. Experience : 3.5 - 6 years Position : AI Engineer Skills Required : Python, Agentic AI, AI Models, Agentic Framework, Agentic Workflows, Langgraph OR CrewAI, Open source, data science Exposure Role and Responsibilities Architect and build a reusable, secure, and scalable Agentic AI framework that can be adopted by multiple teams across the enterprise. Define standards, patterns, and abstractions for building intelligent agents using LLMs and other foundational models. Leverage and extend frameworks like LangGraph, CrewAI, or Semantic Kernel to enable advanced agentic capabilities such as (Long-horizon task planning, Tool calling (APIs, databases, RPA, internal services), Memory persistence and retrieval (via vector stores or knowledge graphs),Autonomous decision-making and reflection,Multi-agent orchestration and collaboration, Human-in-the-loop workflows,Monitoring and observability,Governance and compliance,Security and access control,Performance optimization and cost management Collaborate with cross-functional teams to ensure the framework aligns with enterprise-grade expectations. Integrate the framework with existing enterprise platforms. Conduct research and stay updated on the latest advancements in Agentic AI, LLMs, and related technologies. Mentor and guide junior engineers in best practices for building agentic systems. Coach and guide engineering teams in adopting and extending the framework. Show more Show less

As an AI/ML Engineer Generative AI Specialist with over 5 years of experience, you will be expected to possess the following must-have skills: You should have a strong background in AI/ML frameworks such as PyTorch, TensorFlow, and proficient in Python programming. Your experience with AWS services, specifically AWS Bedrock and Lambda functions, will be crucial. Hands-on expertise in LangChain components (agents, chains, memories, parsers, document loaders), developing and optimizing GenAI, NLP models, and CrewAI is essential for this role. You should be capable of building and deploying RAG (Retrieval-Augmented Generation) systems, chatbots, and AI applications using OpenAI APIs, Ollama, Llama, and llamaparse. Advanced prompt engineering techniques like Chain of Thought (CoT) prompting should be within your skill set. Additionally, experience with Docker, CI/CD pipelines, YML files, and GitHub repository management is required. A strong understanding of system design principles, focusing on security, scalability, and performance optimization, is a must. Good-to-have skills include experience in responsible AI practices, knowledge of event-driven architecture, and familiarity with cloud deployments and Kubernetes. Experience with large-scale AI model training and fine-tuning would be beneficial. Your key responsibilities will involve designing and implementing AI/ML solutions using cutting-edge technologies to ensure scalability, efficiency, and alignment with business objectives. You will be responsible for developing and optimizing LangChain components, CrewAI, GenAI, and NLP models customized to specific applications. Building and deploying production-ready RAG systems, chatbots, and AI-driven applications utilizing OpenAI APIs, Ollama, Llama, and llamaparse will be part of your role. Leveraging AWS Bedrock and other AWS services to deliver high-performance AI solutions is crucial. You will need to apply prompt engineering techniques like Chain of Thought (CoT) prompting to enhance AI interactions, maintain CI/CD pipelines, manage YML files, and utilize GitHub for version control. Implementing containerization using Docker and deploying AI solutions in cloud environments will also fall under your responsibilities. Ensuring that solutions adhere to best practices in system design, focusing on security, performance, and efficiency considerations is essential. You will also need to incorporate responsible AI practices and ensure compliance with ethical AI guidelines. Collaboration with cross-functional teams to translate AI insights into impactful solutions and effective communication of complex technical concepts to both technical and non-technical stakeholders will be expected from you.,

Must Have Skills: 2+ years of hands-on experience in agentic AI / multi-agent systems. Proficiency with LangChain, Langraph, CrewAI, AutoGen, Haystack, or equivalent frameworks. Strong background in Python and experience with prompt engineering, tools integration, and chaining logic. Solid understanding of LLM APIs, RAG, vector stores, tool use, and memory architectures. Hands-on experience with open-source and commercial LLMs (e.g., GPT-4, Claude, Gemini, Mistral). Experience deploying AI agents in cloud-native environments (AWS, GCP, Azure). Ability to lead architectural discussions, PoCs, and hands-on development in fast-paced environments. Model-cost profiling and budgeting (API call minimization, batch vs. streaming) Latency tuning for real-time agents, Autoscaling strategies." Exposure to Autonomous AI agents (AutoGPT, BabyAGI, CAMEL, MetaGPT). Understanding of LLM fine-tuning, adapters, and RLHF. Experience with agent simulation, environment modeling, or reinforcement learning is a plus. Familiarity with compliance, privacy, and safety in GenAI deployments. Prior experience in building domain-specific agents (Lifescience, healthcare, Pharma). Key Responsibilities: Architect and implement agentic AI systems using modern LLM orchestration frameworks (LangChain, CrewAI, AutoGen, etc.). Design multi-agent collaboration models including planner-solver, autonomous teams, and goal decomposition agents. Build reusable tooling, APIs, and memory architectures for agent interaction, coordination, and context persistence. Lead hands-on development and deployment of GenAI applications (e.g., assistants, copilots, decision support). Evaluate and integrate LLMs (OpenAI, Claude, Mistral, LLaMA, etc.), vector databases (Pinecone, Weaviate, FAISS), and retrieval systems (RAG). Optimize agent performance for real-time environments, reliability, scalability, and ethical constraints. Guide teams in adopting agent frameworks, best practices, prompt engineering, and model fine-tuning. Collaborate with stakeholders to translate business requirements into technical solutions using agent-based paradigms. Continuously monitor trends in multi-agent systems, cognitive architectures, and open-source AI frameworks.

Mandatory Skills: 1. 5+ Years of experience in the design & development of state-of-the-art language models; utilize off-the-shelf LLM services, such as Azure OpenAI, to integrate LLM capabilities into applications. 2. Deep understanding of language models and a strong proficiency in designing and implementing RAG-based workflows to enhance content generation and information retrieval. 3. Experience in building, customizing and fine-tuning LLMs via OpenAI studio extended through Azure OpenAI cognitive services for rapid PoCs 4. Proven track record of successfully deploying and optimizing LLM models in the cloud (AWS, Azure, or GCP) for inference in production environments and proven ability to optimize LLM models for inference speed, memory efficiency, and resource utilization. 5. Apply prompt engineering techniques to design refined and contextually relevant prompts for language models. 6. Monitor and analyze the performance of LLMs by experimenting with various prompts, evaluating results, and refining strategies accordingly. 7. Building customizable, conversable AI agents for complex tasks using CrewAI and LangGraph to enhance Gen AI solutions 8. Proficient in MCP (Model Context Protocol) for optimizing context-aware AI model performance and integration is a plus Location - Mumbai , Pune, Bangalore, Chennai and Noida

Short Description Description About Oracle Customer Success Services Oracle University & the Role It is an exciting time to be part of Oracle Customer Success Services (CSS) Oracle University. As Oracle continues to rapidly introduce new products and enhancements, our focus is on delivering world class training solutions for next-generation AI capabilities that automate and revolutionize business processes across industries. The Fusion Cloud Applications Product Management Team within Oracle University is instrumental in setting the learner journey direction aligned to the innovative Fusion Cloud Applications AI initiative , and we are seeking a highly skilled, visionary Solution Lead with deep expertise in Oracle Fusion Cloud Applications and AI-driven solutions. This unique opportunity blends technical leadership, consulting, enablement, curriculum strategy, and hands-on innovation. You will shape, deliver, and educate on practical, scalable AI and AI Agent solutions that empower customers and Oracle partners to leverage leading AI capabilitieswhile translating the latest Oracle Fusion Cloud Application AI innovations into actionable training and enablement resources. Responsibilities Key Responsibilities AI Training Strategy and Design Lead the design and deployment of Oracle Fusion Cloud (ERP, HCM, SCM, CX) solutions by building and integrating the latest AI/ML innovations from Oracles evolving cloud portfolio into innovative training solutions. Consult closely with product development on the end-to-end implementation of practical AI agent applications, ensuring alignment with business objectives and industry best practices to include in OU training catalog. Serve as a subject matter expert and technical advisor, guiding customers and systems integrator partners on effectively implementing, tailoring, and operationalizing AI agent templates via OU training catalog. Advisory, & Best Practice Development Engage directly with Product Development to define training requirements, use cases, and desired AI outcomestranslating these needs into hands-on, deployable technical training solutions. Document and curate AI agent best practices, use cases, and lessons learned, elevating OU learners understanding and adoption of AI-powered enterprise solutions. Provide actionable feedback to CSS OU teams based on real-world AI agent deployments and customer interactions to continually evolve and enhance training. Partner & Customer Enablement: Training and Curriculum Leadership Act as an AI evangelist and enablement leaderdesign, develop, and continuously update comprehensive training curriculum and enablement resources focused on Oracle Fusion Cloud Applications AI capabilities for Oracle partners and customers. Proactively track and evaluate new Oracle Fusion Cloud AI features and innovations, translating advancements into high-impact internal and external enablement programs, workshops, documentation, and learning content. Innovation, Collaboration & Continuous Improvement Collaborate cross-functionally with Oracle product development and curriculum teams to innovate and refine agent-based cloud solutions, remaining hands-on and current in advanced AI and analytics trends. Lead continuous process and content improvement by gathering and analyzing stakeholder feedback, iterating training materials and curriculum as Oracles AI portfolio advances. Use project management and analytics tools to transparently track deliverables, monitor program and curriculum success, and measure overall business impact. Required Qualifications Bachelors or Masters degree in Computer Science, Software Engineering, Advanced Analytics, Information Systems, or a related STEM field. Experience working directly with customers, partners, and sales teams to deliver tailored technical solutions and advisory services Strong background in computer science, technical solution engineering, or advanced analytics. Understanding of RAG (Retrieval-Augmented Generation) techniques is required. Experience in designing and building AI multi-agent solutions for business environments is a plus Has built and deployed enterprise applications, including experience in solution engineering, building functional and/or technical demonstrations, consulting, or software development. Hands-on experience implementing scalable AI systems is desired though not required. Ability to understand, clarify, and translate functional/business requirements into practical, viable training solutions Experience leading Oracle Fusion Cloud Application implementations (ERP, HCM, SCM, CX) focusing on AI and enterprise innovation Demonstrated hands-on experience architecting, building, and deploying enterprise-class cloud and AI/ML solutionsparticularly within Oracle Fusion Cloud and/or analogous ERP, HCM, SCM, CX platforms. Expertise in the design of functional/technical curriculum and enablement material. Proficiency with frameworks such as Flowise, CrewAI, Relevance AI, Langchain, or AutoGen. Ability to consult, advise, and collaborate directly with enterprise customers, SI partners, and Oracle sales teams to deliver tailored, high-impact AI and cloud solutions. Outstanding communication skills (oral, written, and presentation), strong analytical and critical thinking skills, and the ability to proactively solve complex problems. Experience working in a fast-paced, dynamic software/cloud environment. Preferred Qualifications Oracle Cloud Architect and/or relevant Functional certifications. Experience enabling Oracle partners/customers in deploying and adopting AI or automation-driven cloud solutions. Previous involvement in change management and user adoption programs for enterprise systems. Knowledge of hybrid and multi-cloud architectures. Show more Show less

Backend Engineer (Python, Node Js, Agentic AI) Exp : 3 - 7 yrs Location: Pune Min 3 yrs exp in Backend developer exposure to AI/ML Min 2+ yrs exp in backend development using Python and Node.js For JD, write to amit.gaine@talentxo.in

The role involves working on Agentic AI Platform Delivery where you will be responsible for developing and maintaining autonomous software agents using modern LLM frameworks. You will also be required to build reusable components for business process automation, design agent orchestration, prompt engineering, and LLM integrations, as well as enable deployment across CRM systems and enterprise data platforms. Additionally, you will work on Generative AI & Model Optimization by fine-tuning LLMs/SLMs with proprietary NBFC data, and focusing on model distillation, quantization, and edge deployment readiness. Moreover, you will be creating self-learning systems by developing adaptive frameworks that learn from interaction outcomes and implementing lightweight models to support real-time decision-making. The ideal candidate for this position should hold a B.E./B.Tech/M.Tech degree in Computer Science or a related field, with a minimum of 3-7 years of experience in AI/ML roles. Proficiency in languages such as Python, Node.JS, JavaScript, React, and Java is required, along with experience in using tools/frameworks like LangChain, Semantic Kernel, LangGraph, and CrewAI. Familiarity with platforms such as GCP, MS Foundry, Copilot Studio, BigQuery, and Power Apps/BI is essential. Knowledge of Agent Tools like Agent Development Kit (ADK) and Multi-agent Communication Protocol (MCP), as well as a strong understanding of prompt engineering, LLM integration, and orchestration, are also expected. In addition to the technical requirements, the candidate should possess strong communication skills, teamwork abilities, and problem-solving capabilities. Being proactive, detail-oriented, and able to work under pressure are desirable traits for this role. Joining this dynamic team at Bajaj Finance Limited offers numerous perks, benefits, and a vibrant work culture. The company values its employees and recognizes their contributions, making it a rewarding and challenging environment to grow and excel. With a presence in over 500 locations across India, you will have the opportunity to be part of one of Asia's top 10 Large workplaces and contribute to the success and innovation of a leading Non-banking financial company.,

#GenerativeAI Experts ready for AI race, this is for you! Announcing Hexaware conducting Walkin Drive for AI Engineer and Lead Data Scientist (GenAI)-Noida Location-3rd Aug 2025(Sunday) Interested candidates share your CV at umaparvathyc@hexaware.com Open Positions: AI Engineer/Lead Data Scientist (GenAI) AI Engineer Experience- 3+years Lead Data Scientist (GenAI) Experience- 7+years Notice Period- 15 days/30days Max (who serving Notice Period) Walkin Drive Location- Noida Date of drive- 3rd Aug 2025(Sunday) Must have Experience: LLM, Advance RAG, NLP, transformer model, LangChain Technical Skill: 1. Strong Experience in Data Scientist (GENAI) 2. Proficiency with Generative AI models like GANs, VAEs, and transformers 3. Expertise with cloud platforms (AWS, Azure, Google Cloud) for deploying AI models 4. Strong Python Fast API experience, SDA based implementations for all the APIs 5. Knowledge of Agentic AI concepts and applications

You will be part of a team that is building an Agentic AI Platform aimed at enabling enterprises to solve real business problems using Agentic AI workflows. The platform covers a wide range of areas from utility operations to legal document review. The ultimate goal is to empower AI agents to think, act, and deliver quickly, securely, and locally. As an Agentic AI Engineer, you will have the opportunity to work with cutting-edge frameworks such as Lang Chain, CrewAI, Lang Graph, Google ADK, and more. Your role will involve translating real enterprise challenges into intelligent multi-agent workflows. Your responsibilities will include building and deploying AI agents using open-source agentic frameworks, integrating models from sources like OpenAI, Mistral, Gemini, Llama, Claude, among others, and utilizing tools such as Retrieval-Augmented Generation (RAG), knowledge graphs, and vector stores. Collaboration with product managers and domain experts to address real problems in various enterprise domains like utilities, legal, marketing, and supply chain will be a key aspect of your role. Additionally, you will play a significant role in continuously testing and refining agent behavior and contributing to the enhancement of the proprietary DataInsightAI platform. To excel in this role, you should possess at least 1+ years of hands-on experience in implementing enterprise-level Gen AI projects that have been successfully deployed. Strong Python skills, familiarity with LLMs, agentic AI workflows, RAG, vector databases, and the ability to simplify complex problems are essential. A curiosity-driven mindset, a fast learner, and hands-on coding abilities are also crucial for success in this role. While not mandatory, experience in multi-agent architectures, graph databases like Neo4j, deployment on cloud platforms such as Azure/AWS/GCP, and familiarity with LangGraph or Google ADK are considered advantageous. Joining our team will offer you the opportunity to work on cutting-edge agentic AI projects daily, be part of a small team with significant ownership, ship solutions rapidly, and tackle real enterprise challenges. Moreover, you will be supported by InTimeTec, a company with a strong AI/ML engineering culture.,

You should have 3 to 10 years of experience in AI development and be located in Coimbatore. Immediate joiners are preferred. A minimum of 2 years of experience in core Gen AI is required. As an AI Developer, your responsibilities will include designing, developing, and fine-tuning Large Language Models (LLMs) for various in-house applications. You will implement and optimize Retrieval-Augmented Generation (RAG) techniques to enhance AI response quality. Additionally, you will develop and deploy Agentic AI systems capable of autonomous decision-making and task execution. Building and managing data pipelines for processing, transforming, and feeding structured/unstructured data into AI models will be part of your role. It is essential to ensure scalability, performance, and security of AI-driven solutions in production environments. Collaboration with cross-functional teams, including data engineers, software developers, and product managers, is expected. You will conduct experiments and evaluations to improve AI system accuracy and efficiency while staying updated with the latest advancements in AI/ML research, open-source models, and industry best practices. You should have strong experience in LLM fine-tuning using frameworks like Hugging Face, DeepSpeed, or LoRA/PEFT. Hands-on experience with RAG architectures, including vector databases such as Pinecone, ChromaDB, Weaviate, OpenSearch, and FAISS, is required. Experience in building AI agents using LangChain, LangGraph, CrewAI, AutoGPT, or similar frameworks is preferred. Proficiency in Python and deep learning frameworks like PyTorch or TensorFlow is necessary. Experience in Python web frameworks such as FastAPI, Django, or Flask is expected. You should also have experience in designing and managing data pipelines using tools like Apache Airflow, Kafka, or Spark. Knowledge of cloud platforms (AWS/GCP/Azure) and containerization technologies (Docker, Kubernetes) is essential. Familiarity with LLM APIs (OpenAI, Anthropic, Mistral, Cohere, Llama, etc.) and their integration in applications is a plus. A strong understanding of vector search, embedding models, and hybrid retrieval techniques is required. Experience with optimizing inference and serving AI models in real-time production systems is beneficial. Experience with multi-modal AI (text, image, audio) and familiarity with privacy-preserving AI techniques and responsible AI frameworks are desirable. Understanding of MLOps best practices, including model versioning, monitoring, and deployment automation, is a plus. Skills required for this role include PyTorch, RAG architectures, OpenSearch, Weaviate, Docker, LLM fine-tuning, ChromaDB, Apache Airflow, LoRA, Python, hybrid retrieval techniques, Django, GCP, CrewAI, OpenAI, Hugging Face, Gen AI, Pinecone, FAISS, AWS, AutoGPT, embedding models, Flask, FastAPI, LLM APIs, DeepSpeed, vector search, PEFT, LangChain, Azure, Spark, Kubernetes, AI Gen, TensorFlow, real-time production systems, LangGraph, and Kafka.,

As a Senior Generative AI Engineer, your primary role will involve conducting original research on generative AI models. You will focus on exploring model architecture, training methodologies, fine-tuning techniques, and evaluation strategies. It is essential to maintain a strong publication record in esteemed conferences and journals, demonstrating your valuable contributions to the fields of Natural Language Processing (NLP), Deep Learning (DL), and Machine Learning (ML). In addition, you will be responsible for designing and experimenting with multimodal generative models that incorporate various data types such as text, images, and other modalities to enhance AI capabilities. Your expertise will be crucial in developing autonomous AI systems that exhibit agentic behavior, enabling them to make independent decisions and adapt to dynamic environments. Leading the design, development, and implementation of generative AI models and systems will be a key aspect of your role. This involves selecting suitable models, training them on extensive datasets, fine-tuning hyperparameters, and optimizing overall performance. It is imperative to have a deep understanding of the problem domain to ensure effective model development and implementation. Furthermore, you will be tasked with optimizing generative AI algorithms to enhance their efficiency, scalability, and computational performance. Techniques such as parallelization, distributed computing, and hardware acceleration will be utilized to maximize the capabilities of modern computing architectures. Managing large datasets through data preprocessing and feature engineering to extract critical information for generative AI models will also be a crucial aspect of your responsibilities. Your role will also involve evaluating the performance of generative AI models using relevant metrics and validation techniques. By conducting experiments, analyzing results, and iteratively refining models, you will work towards achieving desired performance benchmarks. Providing technical leadership and mentorship to junior team members, guiding their development in generative AI, will also be part of your responsibilities. Documenting research findings, model architectures, methodologies, and experimental results thoroughly is essential. You will prepare technical reports, presentations, and whitepapers to effectively communicate insights and findings to stakeholders. Additionally, staying updated on the latest advancements in generative AI by reading research papers, attending conferences, and engaging with relevant communities is crucial to foster a culture of learning and innovation within the team. Mandatory technical skills for this role include strong programming abilities in Python and familiarity with frameworks like PyTorch or TensorFlow. In-depth knowledge of Deep Learning concepts such as CNN, RNN, LSTM, Transformers LLMs (BERT, GEPT, etc.), and NLP algorithms is required. Experience with frameworks like Langgraph, CrewAI, or Autogen for developing, deploying, and evaluating AI agents is also essential. Preferred technical skills include expertise in cloud computing, particularly with Google/AWS/Azure Cloud Platform, and understanding Data Analytics Services offered by these platforms. Hands-on experience with ML platforms like GCP: Vertex AI, Azure: AI Foundry, or AWS SageMaker is desirable. Strong communication skills, the ability to work independently with minimal supervision, and a proactive approach to escalate when necessary are also key attributes for this role. If you have a Master's or PhD degree in Computer Science and 6 to 8 years of experience with a strong record of publications in top-tier conferences and journals, this role could be a great fit for you. Preference will be given to research scholars from esteemed institutions like IITs, NITs, and IIITs.,

Work Location: Bangalore (in-office) We're seeking hands-on Lead Software Engineers who can: Build production-ready AI solutions on AWS Guide distributed teams while continuously scouting and prototyping emerging AI technologies You'll join our Product Engineering group, owning end-to-end delivery of next-generation Amorphic AI solutions while mentoring engineers across global teams. What is Expected: Technical Leadership Lead the integration of cutting-edge AI/LLMs into Amorphic AI Solutions, ensuring seamless interoperability and optimal performance Design and architect complex software systems with focus on scalability, maintainability, and performance Architect production-grade RAG pipelines and multi-agent orchestration on AWS (Lambda, ECS/Fargate, Bedrock, SageMaker, DynamoDB, S3, EventBridge, Step Functions) Drive the design and implementation of scalable AI pipelines Development & Innovation Design, develop, test, and maintain scalable backend applications using Python and AWS services Stay current with AI advancements through hands-on experimentation with emerging frameworks (LangChain, Hugging Face Transformers, CrewAI) via prototypes and side projects Optimize AI solution performance focusing on cost-effectiveness, latency, and resource utilization Develop strategies for monitoring, maintaining, and improving deployed AI models in production Team Leadership Lead 5-10 engineers through design reviews, pair-programming, and PR feedback Conduct code reviews and design discussions to ensure adherence to best practices Collaborate with cross-functional teams globally to identify requirements and implement solutions Create and maintain comprehensive documentation for architecture, design decisions, and coding practices Preferred Candidate Profile BE / B.Tech in Computer Science or related field 8+ years of experience in software development Solid understanding of large language models (LLMs), including experience with prompt engineering, fine-tuning, or integrating LLM APIs (e.g., from OpenAI, Anthropic, or AWS Bedrock) Hands-on experience building AI solutions using latest tools and frameworks (e.g., langchain, crewAI), demonstrated through side projects, open-source contributions, or personal prototypes Proven leadership experience in managing and mentoring high-performing teams of software and application developers Exceptional proficiency in Python programming language Solid understanding of AWS ecosystem including Lambda functions, S3 buckets, EMR clusters, DynamoDB tables etc. Proven experience in a leadership role, leading software development teams in the delivery of complex projects Deep understanding of software architecture and design principles, with a focus on building scalable and maintainable systems Experience with distributed systems, microservices architecture, and cloud-based solutions Strong knowledge of software development best practices, including code reviews, testing, and CI/CD pipelines Experience working with AWS services and developing Cloud Native Applications using REST APIs is must have Experience working in an agile delivery environment, especially product engineering teams How We'll Take Care Of You: We believe in supporting our team members both professionally and personally. Here's a look at the comprehensive benefits and perks we offer: Financial Well-being & Security Competitive Compensation : Enjoy competitive salaries and bonuses that reward your hard work and dedication Robust Insurance Coverage : Benefit from health, life, and disability insurance to ensure you and your family are protected Provident Fund Eligibility : Secure your future with eligibility for the provident fund Work-Life Balance & Flexibility Flexible Working Hours : We offer flexible working hours to help you manage your personal and professional commitments Generous Paid Time Off : Take advantage of unlimited Paid Time Off (PTO), with a mandatory minimum of 1 week per year to ensure you recharge Comprehensive Leave Policies : We provide paid vacation days, sick leave, and holidays, plus supportive parental leave (maternity, paternity, and adoption) and bereavement leave when you need it most Professional Growth & Development Learning & Development : Elevate your skills with access to extensive certification and training programs Cutting-Edge Technologies : You'll work at the forefront of innovation with cutting-edge technologies, constantly igniting your passion for continuous learning and growth Culture & Community Recognition & Rewards : Your contributions won't go unnoticed with our recognition and reward programs Engaging Activities : Connect with your colleagues through company-sponsored events, outings, team-building activities, and retreats .

We are looking for a Technical Architect who has experience designing software solutions from the ground up, making high-level decisions about each stage of the process and leading a team of engineers to create the final product. To be successful as a Technical Architect, you should be an expert problem solver with a strong understanding of the broad range of software technologies and platforms available. Top candidates will also be excellent leaders and communicators. Responsibilities Collaborate with stakeholders (Product Owners, Engineers, Clients) to define and refine software architecture aligned with product vision. Design scalable, modular, and secure system architecture using microservices and modern design patterns. Create high-level product specifications, architecture diagrams, and technical documentation. Provide architectural blueprints, guidance, and technical leadership to development teams. Build and integrate AI-driven components, including Agentic AI (AutoGen, LangGraph), RAG pipelines, and LLM capabilities (Open-source and Commercial models). Define vector-based data pipelines and integrate vector databases such as FAISS, ChromaDB, or Azure AI Search. Lead the implementation of Prompt Engineering strategies to optimize LLM outcomes. Architect and deploy scalable, secure solutions on Azure Cloud, using services like Azure Kubernetes Service (AKS), Azure Functions, Azure Storage, and Azure DevOps. Ensure robust CI/CD and DevSecOps practices in place to streamline deployments and enforce compliance. Guide the team in troubleshooting, code reviews, performance tuning, and ensuring adherence to software engineering best practices. Conduct regular technical reviews, present progress updates, and ensure timely delivery of milestones. Drive innovation and exploration of emerging technologies, particularly in the field of Generative AI and Intelligent Automation. Requirements 10+ years of hands-on software development experience, with a strong Python background. 3+ years of experience in a Software or Solution Architect role. Proven experience in designing and building production-grade solutions using microservices architecture. Strong expertise in Agentic AI frameworks (AutoGen, LangGraph, CrewAI, LangChain, etc.). Working knowledge of LLMs (Open-source like LLaMA, Mistral; Commercial like OpenAI, Azure OpenAI). Solid experience with Prompt Engineering, RAG pipelines, and Vector Database integration. Experience deploying AI/ML solutions on Azure Cloud, leveraging PaaS components and cloud-native patterns. Proficiency with containerization and orchestration tools (Docker, Kubernetes). Knowledge of architectural patterns: event-driven, domain-driven design, CQRS, service mesh, etc. Familiarity with NLP tools, frameworks, and libraries (spaCy, Hugging Face, Transformers, etc.). Experience with Apache Airflow or other workflow orchestration tools. Strong communication and leadership skills to work cross-functionally with technical and non-technical teams.

58 years of experience in AI/ML or automation engineering. Strong hands-on experience with CrewAI or other LLM orchestration frameworks like LangChain, AutoGen, or Semantic Kernel. Proficiency in Python, including experience with async programming and API integration. Deep understanding of LLMs (OpenAI, Anthropic, Mistral, etc.) and prompt engineering. Familiarity with vector databases (e.g., Pinecone, FAISS, Chroma) and embeddings. Experience building and deploying production-ready agent-based solutions. Strong problem-solving skills and ability to translate business requirements into technical implementations.